We're pleased to announce the program for the 2nd Annual Politics and
Computational Social Science (PACSS) Conference to be held Wednesday
August 28 @ Georgetown University.
Details are below and at https://mccourt.georgetown.edu/PaCSS
Register for the conference at ourregistration page
<https://www.eventbrite.com/e/politics-and-computational-social-science-pacss-conference-tickets-58392910768>.
Registration is $50 before August 12, 2019 and $100 after that.*Seating
is limited, so please register early to ensure space*. The conference
includes breakfast, lunch, coffee, snacks and a reception with bar and
hors d’ oeuvres.
Pew Research Center is pleased to hosttwo parallel training workshops
<https://mccourt.georgetown.edu/PaCSS#workshops> at their office in
downtown D.C. These workshops will focus on two key areas: 1) natural
language (NLP) processing techniques and their application to social
science questions; and 2) deep learning techniques with applications to
image analysis for social scientists. Participants will be given
hands-on experience building and training models in these subject areas
and will also be able to meet members of Pew Research Center’sData Labs
team <https://www.pewresearch.org/topics/data-labs/>. Workshops will run
from 2pm to 5pm Tuesday August 27. Light snacks and coffee will be
provided. Cost per participant is $25.
Please email me at [log in to unmask] if you have any
questions. Other organizers are David Lazer and Sarah Shugars, both from
Northeastern University.
Preliminary Conference Program: Wednesday, August 28, 2019
**Exact times subject to change - please check final schedule to be
posted later**
*8:45am—9:15am*
*Welcoming Remarks*
*9:15am—10:30am*
*Networks <https://mccourt.georgetown.edu/PaCSS#networks> | Social
Media <https://mccourt.georgetown.edu/PaCSS#sm> | NLP
<https://mccourt.georgetown.edu/PaCSS#nlp>*
*10:30am—10:50am*
*Break*
*10:50am—12:05pm*
*Methods in CSS <https://mccourt.georgetown.edu/PaCSS#methods> | The
News <https://mccourt.georgetown.edu/PaCSS#news> | Image
<https://mccourt.georgetown.edu/PaCSS#image>*
*12:05pm—1:30pm*
*Lunch & Business Meeting*
*1:30pm—2:45pm*
*IR <https://mccourt.georgetown.edu/PaCSS#ir> | Journalism
<https://mccourt.georgetown.edu/PaCSS#journalism> | Video
<https://mccourt.georgetown.edu/PaCSS#video>*
*2:45pm—3:00pm*
*Break*
*3:00pm—4:15pm*
*Attitudes & Beliefs <https://mccourt.georgetown.edu/PaCSS#attitudes> |
Campaigns <https://mccourt.georgetown.edu/PaCSS#campaigns> | Machine
Learning <https://mccourt.georgetown.edu/PaCSS#ml>*
*4:15pm—4:30pm*
*Break*
*4:30pm—5:30pm*
*Keynote Address: *Sandra González-Bailón, University of Pennsylvania
<https://www.asc.upenn.edu/node/648>
*5:30pm—7:00pm*
*Poster Sessions & Reception*
9:15am-10:30am
Networks:
* /Legislative communication style: linking legislators across medium
and message/
Rachel Blum, Miami University
* /Network Event History Analysis for Modeling Public Policy Adoption
with Latent Diffusion Networks/
Bruce Desmarais, Pennsylvania State University
* /Target Policymaking Under the Frame of Dark Networks: Strengths,
Weaknesses and Opportunities/
Joseph Shaheen, George Mason University
* /Failure to Communicate: Individual Reasoning Structure and
Deliberative Outcomes/
Sarah Shugars, Northeastern University
Social Media:
* /Knowledge Decays: Temporal Validity in Online Social Science/
Kevin Munger, Penn State University
* /Social Media Markets for Survey Research in Comparative Contexts:
Facebook Users in Kenya/
Leah Rosenzweig, Institute for Advanced Study in Toulouse (IAST)
* /The Influencer Ecosystem in the 2018 U.S. Primaries/
Yotam Shmargad, University of Arizona
* /Journalists on Twitter: Self-branding, Audiences, and Involvement
of Bot/
Onur Varol, Northeastern University
NLP:
* /A Bayesian Transition Network Topic Model for Inferring Conceptual
Networks/
Nick Beauchamp, Northeastern University
* /The Mechanics of Emergent Political Voice/
Amy Magnus, Air Force Institute of Technology
* /Humans and Machines Learning Together/
Stuart Shulman, Texifter
* /The Digital Pulpit: A Nationwide Analysis of Online Sermons/
Dennis Quinn, Pew Research Center
10:50am-12:05pm
Methods in Conputational Social Science:
* /311: What's Your Emergency?/
Rebekah Getman, Northeastern University
* /Shifting Sands: An Agent-Based Model of Mobilization Against a
Central Authority/
Soha Hammam, Claremont Graduate University
* /Analyzing Link Sharing Across Platforms to Study Political
Messaging and Ideology/
Joshua Tucker, NYU
* /Event Data with Images/
Zachary Steinert-Threlkeld, UCLA
The News:
* /The Distorting Prism of Social Media: How Online Comments Amplify
Toxicity/
Jin Woo Kim, Dartmouth College
* /Affective Polarization in Online Uncivil Comments/
Yujin Kim, University of Texas at Austin
* /Nationalized news: using large-scale collections of close captions
text to identify national network stories in local news broadcasts/
Pavel Oleinikov, Wesleyan University
* /Measuring the European public sphere across multiple languages/
Maurits van der Veen, College of William & Mary
Image:
* /Ideological Scaling of Political Images/
Jason Anastasopoulos, University of Georgia
* /Using Computer Vision to Capture the Collective Perception of a
Neighborhood/
Laura Nelson, Northeastern University
* /How do Machines See Gender? Demystifying a machine vision system/
Emma Remy, Pew Research Center
* /Do Women Candidates “Run as Women” Online? An Automated Image and
Text Analysis of Campaign Advertising on Facebook and TV/
Jielu Yao, Wesleyan University & University of Iowa
1:30pm-2:45pm
IR:
* /Text-Based Approaches to Analyzing Group Behavior in Conflict Setting/
Margaret Foster, Duke University
* /Where the money blows – Using speeches to identify the effect of
Chinese foreign aid on the US-African relationship structure/
Dennis Hammerschmidt, University of Mannheim
* /Detecting Foreign Influence Operations’ Content on Social Media/
Meysam Alizadeh, Princeton University
* /Measuring a Threat Perception: Text Analysis of the Speech Records
of the United Nations Security Council, 1994-2019/
Takuto Sakamoto, University of Tokyo
Journalism:
* /Systematic biases in local news search results: an audit study/
Sean Fischer, University of Pennsylvania
* /Can Digital Literacy Save Us from Fake News? Evidence from the U.S./
Andy Guess, Princeton University
* /Online Information Seeking during the 2018 U.S. Congressional
Elections/
Ronald Robertson, Northeastern University
* /How Does the Media Environment Affect Readership? Evidence from an
App Patient-Preferred Trial in Italy/
Alessandro Vecchiato, Stanford
Video:
* /Automated Coding of Political Campaign Advertisement Videos: A
Validation Study/
Wonjoon Hwang, Harvard University
* /Comparing Human and Machine Classification of Written and Video
Records of Parliamentary Debates/
Christopher Cochrane, University of Toronto
* /How Online Propaganda Radicalizes Foreign Citizens/
Tamar Mitts, Columbia University
* /Mapping Extremist Networks with Visual Imagery/
Rob Williams, UNC Chapel Hill
3:00pm-4:15pm
Attitudes & Beliefs:
* /Religiosity and Public Policy in Congress: Analyzing the partisan
dimensions of legislators’ religious rhetoric/
Sarah Dreier, University of Washington
* /Gender Norms and Violent Behavior in a Virtual World/
Eric Dunford, Georgetown University
* /Ecologies of Online Contention: From Hate to Health/
Neil Johnson, George Washington University
* /Can Celebrities Reduce Prejudice? The Effect of Mohamed Salah on
Islamophobic Attitudes and Behaviors/
Alexandra Siegel, Stanford University
Campaigns:
* /Downsian Convergence on Non-Policy Issues: Evidence from Campaign
Manifestos at French Legislative Elections/
Caroline Le Pennec, University of California, Berkeley
* /The Supply and Demand of Fact v. Opinion in Presidential Tweets/
Stan Oklobdzija, Claremont McKenna College
* /From Home Base to Swing States: Spatio-temporal Analysis of
Political Advertising Strategies/
Piotr Sapiezynski, Northeastern University
* /Pandering Politicians: Ideological Changes from Primary to General
Elections/
Ye Wang, New York University
Machine Learning:
* /Automated Visual Clustering: A Technique for Image Corpus
Exploration and Annotation Cost Reduction/
Kevin Aslett, University of Washington
* /Active Learning for Probabilistic Record Linkage/
Ted Enamorado, University of North Carolina at Chapel Hill
* /Data-driven causal inference for applications in political economy/
Daniel Malinsky, Johns Hopkins University
* /A Computational Social Science Approach to Financial Regulation/
Sharyn O'Halloran, Columbia University
--
Michael Bailey <https://michaelbailey.georgetown.domains>
Walsh Professor, Department of Government and McCourt School of Public
Policy
Georgetown University
Real Stats
<https://global.oup.com/academic/product/real-stats-9780199981946?cc=us&lang=en&>
Real Econometrics
<https://global.oup.com/academic/product/real-econometrics-9780190857462?q=michael%20bailey&lang=en&cc=us#>
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